In a previous post, we explained that increasingly the long-term business success in today’s data-driven economy will center on an organization’s analytics maturity.

The first stage of the Analytics Maturity Model, “Measure,” enables executives and front-line managers to get a quick, current status of the operational performance and the business performance of their company.

Many enterprise organizations have historically measured performance using business intelligence (BI) reports. And while traditional BI does meet the basic definition of “Measure,” it certainly doesn’t meet the agility and interactivity of today’s data discovery analytics and mobile technology.

What is needed? In today’s ever-changing business environment, executives and employees practicing strong Measure techniques should use analytics to always keep their fingers on the pulse of the business.

They need the ability to gauge their companies’ vital signs at any time, wherever and whenever they need them – whether it’s in the office on a desktop computer, at a child’s Little League game using a smartphone, or on a flight with a tablet.

And ideally, these metrics should meet the individual needs of each knowledge worker. With personalized KPIs (key performance indicators), each knowledge worker can manage his area of operation by focusing in on the exceptions, i.e., those areas where performance is not living up to expectation or desire.

The easy interactivity of analytics software can offer quick answers to organizational leaders and employees in the Measure stage. For instance, a sales chief for a national electronics retailer can use data visualizations to intuitively switch views from focusing on a sales forecast of all areas to easily filtering different regions in or out to focus more closely on individual teams.

Every Monday morning, Procter & Gamble business and functional leaders start the week by examining the status of how the company is performing in critical business and operational areas. By starting with the step of Measure, the team manages the business by exception, identifying areas where they want to more deeply focus their analytics.

“Measure” is the springboard for deeper data discovery and diagnosis. When organizations understand the status of their operations, they know where to focus their attention for the next phase of analysis, “Diagnose,” to discover the whys behind business and operational performance.

In our next installment in this series, we’ll examine how the highly visual and interactive nature of analytics enables decision makers to quickly and easily explore the root causes that are influencing the performance of the business as well as the operational performance.